Various solutions allowing recognition of characters traced manually on an input zone of a user device are known. Currently available solutions are particularly used for allowing manual input of data, without using a keyboard, in electronic devices, particularly portable electronic devices such as cellular phones, Personal Digital Assistants (PDAs), and the like.
One current solution provides complex recognition algorithms based on a dot matrix or bitmap image of the traced character, which is compared to the model data of a predetermined set of characters to identify the character closest to the trace performed. This solution is impractical and often much too heavy and demanding in terms of computational time and power to be applied in mobile devices which have limited processing capabilities. Another drawback of this solution lies in the fact that it requires a large memory space for defining the characters to be recognized.
Given the complexity and the strong similarity of certain characters, the current practice is to adopt certain simplifications in the set of characters (for example breaking down the characters into different sets of alphabetic characters, numerical characters, symbolic characters, etc., particularly in order to avoid confusion between certain characters such as “O” and “0”, “B” and “8”, “+” and “T”, etc.) and to force the user to trace the characters in accordance with well determined sequences which are sometimes contrary to his normal practice or even any normal practice. Thus, with the existing solutions, there is often only one possible way of tracing each character so that it is not confused with others. Moreover, the sequences which have to be adopted do not necessarily correspond to the natural trace of the desired character. These difficulties are even greater, given that handwriting characteristics are greatly variable and even completely opposite, for example between the handwriting of a right-handed person and a left-handed person.
Solutions like those described above are limited in that they require learning on the part of the user, often contrary to the user's native writing habits. Many users are reluctant to commit the necessary time to learning the determined patterns, thereby minimizing the appeal of such solutions.
Other current solutions map keypad inputs to predetermined characters. While this type of solution does avoid requiring the user to memorize and adhere to a specific set of tracing motions, this solution is not without its downfalls. One shortcoming of the keypad solution is that a user is required to interface through the keypad instead of through a more user friendly touch input. Another shortcoming is that most user devices provide only a limited number of keys, which means that only a limited number of characters can be mapped to a keyed input or multiple characters must be mapped to the same keyed input.